Vetted Apache Cassandra Professionals

“CTO-focused candidate with experience at foundations evaluating startups, including reviewing technical architectures and coaching teams to refine ideas for better platform fit and synergies. Prioritizes company culture and integrity when choosing leadership roles.”

“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”

“Fitbit engineer who has taken multiple projects from concept to release, including architecting a new warranty-evaluation system that achieved 100% accuracy and saved the company $6M. Interested in exploring startup ideas and emphasizes mission alignment and building strong cross-functional teams.”

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”